Data Analytics Lead Engineer

JobCubby; Irving, Northern (TX, KY); Hybrid; USD 126,000 - 189,000; Full time

Benefits offered by this job

Hybrid work model (3 days in office)

Cloud certification support

Competitive compensation

Job summary

Citi is seeking a Data Analytics Lead Engineer to design, build, and operate scalable data pipelines and cloud-based data architectures within our Lending business, spanning Mortgage and Personal Loans.

This is a hands-on data engineering role where you will develop and maintain production-grade data systems - working across big data platforms, data lakes, and cloud infrastructure - that directly power lending analytics at scale.

Qualifications

• 6+ years of hands-on experience building and managing data pipelines, data warehouses, and data lake solutions.
• Experience with Hadoop, Spark, PySpark, Databricks, Delta Lake, Hive, Impala, and Iceberg.
• Cloud data platforms like Snowflake and Cloudera for ETL and ingestion.
• Fluency in Python, Scala, or Shell scripting for data engineering tasks.
• Strong relational and non-relational data modelling and schema design.
• Workflow scheduling: Autosys or Apache Airflow.
• DevOps practices: version control, testing, monitoring, change management.
• Experience with Tableau or Cognos for data presentation.

Responsibilities

• Build, deploy, and manage end-to-end data pipelines ingesting and delivering large-scale lending data.
• Design scalable cloud data architectures across data lakes, warehouses, and streaming environments.
• Architect data schemas to meet performance and business requirements.
• Write and optimize complex SQL queries for large datasets and distributed processing.
• Monitor data quality across pipelines and resolve operational issues.
• Apply generative AI tools to accelerate coding, querying, and data summarization where appropriate.
• Collaborate with analysts, engineers, and governance teams to translate requirements into solutions.

Skills

Hadoop

Apache Spark

PySpark

Databricks

Delta Lake

Hive

Impala

Iceberg

Snowflake

Cloudera

Python

Scala

Shell

Autosys

Apache Airflow

Tableau

Cognos

MongoDB

HBase

Cassandra

Neo4j

Education

Bachelor's degree

Master's degree preferred

Tools

Databricks

Snowflake

Hadoop

Apache Spark

Airflow

Autosys

Tableau

Cognos

MongoDB

HBase

Cassandra

Neo4j

Job description

Citi is looking for a Data Analytics Lead Engineer to design, build, and operate scalable data pipelines and cloud-based data architectures within our Lending business, spanning Mortgage and Personal Loans. This is a hands-on data engineering role where you will develop and maintain production-grade data systems - working across big data platforms, data lakes, and cloud infrastructure - that directly power lending analytics at scale. You will also bring an understanding of AI and ML integration as an additional capability applied within a strong data engineering foundation.

Responsibilities

• Build, deploy, and manage end-to-end data pipelines that ingest, transform, and deliver large-scale lending datasets across Mortgage and Personal Loans with high reliability and performance.
• Design and implement scalable data architectures on cloud platforms, selecting the right tools and approaches across data lakes, data warehouses, and streaming environments.
• Architect and implement data schemas - choosing from relational, dimensional, normalized, or partitioned models - to meet performance, scalability, and business requirements.
• Write and optimize complex SQL queries against large-scale datasets, applying sound decisions around distributed and parallel processing to improve pipeline efficiency.
• Monitor, diagnose, and resolve operational and data quality issues across pipelines to ensure accuracy, completeness, and timely delivery of data.
• Apply generative AI tools to accelerate core engineering tasks such as code generation, query optimization, and data summarization where appropriate.
• Contribute to data engineering standards and collaborate with Business Analysts, Data Engineers, and Data Governance teams to translate business requirements into robust technical solutions.

Required Qualifications & Skills

• 6+ years of hands-on experience building and managing data pipelines, data warehouses, and data lake solutions using technologies such as Hadoop, Apache Spark, PySpark, Databricks, Delta Lake, Hive, Impala, and Iceberg.
• Practical experience with cloud data platforms including Snowflake, Cloudera, used to build and automate ETL and data ingestion workflows.
• Fluency in one or more scripting languages - Python, Scala, or Shell Scripting - applied actively to data engineering, pipeline development, and automation tasks.
• Strong ability to design and query relational and non-relational data stores, with a clear understanding of schema design trade- offs and data modelling principles.
• Hands-on experience with workflow scheduling tools such as Autosys or Apache Airflow to manage and orchestrate data pipeline execution.
• Confident use of DevOps practices including version control, build tools, unit testing, monitoring, and change management to support reliable and repeatable delivery.
• Experience with data visualization platforms such as Tableau, Cognos to support data presentation and reporting needs.
• A Bachelor's degree or equivalent university qualification; a Master's degree is preferred.

Beneficial Skills & Qualifications

• Exposure to cloud-based AI and ML services such as Amazon SageMaker, Azure Machine Learning, or Google AI Platform, used to integrate predictive models within data pipelines.
• Familiarity with NoSQL database technologies such as HBase, MongoDB, Couchbase, Cassandra, or Neo4j.
• Databricks certification or cloud platform certification in AWS, Azure, or GCP.
• A proactive approach to troubleshooting - able to independently investigate root causes and resolve pipeline or data issues with thoroughness and pace.

What We Offer

At Citi, you will work as a practicing data engineer at the center of one of the world's largest financial institutions, solving complex, real-world data challenges across lending products that serve millions of customers globally. We offer the technical scale and team environment to do meaningful engineering work, alongside the flexibility and investment to support your continued growth.

• Hybrid working model with 3 days in the office and 2 days working remotely, providing flexibility alongside team collaboration.
• Access to large-scale, complex data environments and modern cloud infrastructure where your engineering decisions have direct business impact.
• Continuous learning and technical development support, including backing for cloud and platform certifications relevant to your work.
• A collaborative team of data engineers, analysts, and business partners where hands-on technical contribution is valued and visible.
• Competitive compensation and a comprehensive benefits package designed to support your financial and personal wellbeing.

Job Family Group:

Technology

Job Family:

Data Analytics

Time Type: Full time

Primary Location: Irving Texas United States

Primary Location Full Time Salary Range: $125,760.00 - $188,640.00

In addition to salary, Citi’s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.

Most Relevant Skills

Please see the requirements listed above.

Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

Anticipated Posting Close Date: Sept 09 2026

Automated Processing and AI

We use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi.

Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.

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